Quantitative Heart Testing

ABSTRACT

Heart condition and function can be quantified using repolarization measures and/or repolarization indices derived from a time-frequency transform of an electrocardiogram, e.g., based on points in time associated with the T wave. The electrocardiograms, time-frequency maps derived therefrom, and/or indices obtained by analysis of the time-frequency maps and electrocardiograms may be assembled into a user interface. Further embodiments are described.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. application Ser. No.15/271,155, filed on Sep. 20, 2016, which claims priority to and thebenefit of U.S. Provisional Application No. 62/235,309, filed on Sep.30, 2015, U.S. Provisional Application No. 62/276,596, filed on Jan. 8,2016, U.S. Provisional Application No. 62/276,639, filed on Jan. 8,2016, and U.S. Provisional Application No. 62/321,856, filed on Apr. 13,2016. The disclosures of priority applications are hereby incorporatedherein by reference.

TECHNICAL FIELD

The present disclosure relates generally to heart testing, and moreparticularly to systems, devices, and methods for quantifying and/orvisualizing heart condition.

BACKGROUND

Heart testing for coronary heart disease, myocardial ischemia, and otherabnormal heart conditions is routinely performed using anelectrocardiogram (ECG), which represents electrical potentialsreflecting the electrical activity of the heart measured via electrodesplaced on the patient's skin. The heart's electrical system controlstiming of the heartbeat by sending an electrical signal through thecells of the heart. The heart includes conducting cells for carrying theheart's electrical signal, and muscle cells that contract the chambersof the heart as triggered by the heart's electrical signal. Theelectrical signal starts in a group of cells at the top of the heartcalled the sinoatrial (SA) node. The signal then travels down throughthe heart, conducting cell to conducting cell, triggering first the twoatria and then the two ventricles. Simplified, each heartbeat occurs bythe SA node sending out an electrical impulse. The impulse travelsthrough the upper heart chambers, called “atria”, electricallydepolarizing the atria and causing them to contract. Theatrioventricular (AV) node of the heart, located on the interatrialseptum close to the tricuspid valve, sends an impulse into the lowerchambers of the heart, called “ventricles,” via the His-Purkinje system,causing depolarization and contraction of the ventricles. Following thesubsequent repolarization of the ventricles, the SA node sends anothersignal to the atria to contract, restarting the cycle. This pattern andvariations therein indicative of disease are detectable in an ECG, andallow medically trained personnel to draw inferences about the heart'scondition. However, not every developing abnormality is immediatelyvisible in an ECG, and, consequently, many patients are misdiagnosed ashealthy. Furthermore, although ECGs are nowadays typically recorded anddisplayed electronically, they often go little beyond the printed ECGtraces of the past in the type of information they provide and theintuitiveness and convenience with which such information is presented.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating an example system for quantifyingand visualizing heart condition in accordance with various embodiments.

FIG. 2 is an example ECG, illustrating various segments and points intime used in accordance with various embodiments.

FIGS. 3A and 3B are graphs of an example ECG for a normal heart and ascalogram resulting from its wavelet transform, respectively, inaccordance with one embodiment.

FIGS. 3C and 3D are graphs of an example ECG for an abnormal heart and ascalogram resulting from its wavelet transform, respectively, inaccordance with one embodiment.

FIG. 4 is a flow chart of methods for quantifying and visualizing heartcondition, in accordance with various embodiments.

FIG. 5 is a perspective view of an example heart test device inaccordance with various embodiments.

FIG. 6 is a user interface diagram for an example home screen inaccordance with various embodiments.

FIG. 7 is a user interface diagram showing an example report screen inaccordance with various embodiments.

FIGS. 8A-8C show the energy icon contained in the report screen of FIG.7 in three different states, corresponding to high myocardial energy,moderate myocardial energy, and low myocardial energy in accordance withvarious embodiments.

FIG. 9 is a user interface diagram showing a portion of the examplereport screen of FIG. 7 in a different scrolling position, in accordancewith various embodiments.

FIG. 10 is a user interface diagram showing an example report screenincluding a user-input control for lead selection in accordance withvarious embodiments.

FIG. 11A-11B is a flow chart illustrating an electrocardiographyworkflow in accordance with various embodiments.

FIG. 12 is a block diagram of an example computer system as may serve asprocessing facility in accordance with various embodiments.

DESCRIPTION

Described herein, in various embodiments, are systems, devices, andmethods for enhancing the diagnostic capabilities and utility of ECGsthrough advanced signal processing and through the presentation of datain a meaningful, user-friendly way.

In accordance with various embodiments, ECGs—i.e., time-domain signalsreflecting the electric potential of the heart throughout one or morecardiac cycles—are computationally converted, by a suitabletime-frequency transform, into respective two-dimensional time-frequencymaps. In a “time-frequency map,” as the term is herein broadlyunderstood, the signal value (corresponding, e.g., to a measuredelectric potential) is provided as a function of two independentvariables: time, and a measure of the spectral components of the signalsuch as, e.g., frequency (in the narrower sense) or a scaling factor.For example, in some embodiments, short-time Fourier transform is usedto convert the ECGs into spectrograms, where the signal value is afunction of time and frequency. In other embodiments, the ECGs areconverted by (continuous or discrete) wavelet transform into so-calledscalograms, where the signal value is a function of time and a scalingfactor. More generally, a filter bank may be used to transform the ECGinto a time-frequency representation. For ease of reference, thedimension of the time-frequency map that corresponds to the frequency orscaling factor (or any other measure of the spectral components) isherein generally referred to as the frequency dimension or simplyfrequency.

The time-frequency maps, by themselves or in conjunction with the ECGsfrom which they are derived, may be displayed to a physician (or otherclinical personnel) for interpretation, and/or analyzed automatically toderive quantitative metrics of heart condition and function therefrom.By spreading out the spectral components of the measured ECG signals,the time-frequency maps can visualize information not discernible fromthe ECGs themselves, which can help detect conditions traditionally notdiagnosed based on ECGs, such as, e.g., myocardial ischemia.

It has been found that the signal portion associated with the T wavewithin the ECG, which represents the repolarization of the ventricles,is a particularly suitable indicator of heart condition. Accordingly, invarious embodiments, repolarization measures associated with one or morepoints in time (or ranges in time) within the T wave are determined.More specifically, in some embodiments, the T wave, and one or morerelevant points in time therein, are identified within an ECG, and thetime-frequency map derived from the ECG is then analyzed at the one ormore points in time to determine one or more extrema (i.e., maxima orminima) of the signal value of the time-frequency map across frequency.(The phrase “across frequency,” in this context, means that the maximumor minimum is determined for a fixed point in time from the signal valueof the time-frequency map as a (one-dimensional) function of frequencyonly. By contrast, an extremum determined “across time and frequency” isthe maximum or minimum signal value within the two-dimensionaltime-frequency map (or a two-dimensional portion thereof, e.g., if thetime dimension is limited to an interval).) In certain embodiments,repolarization measures are determined for the point in time where the Twave peaks (i.e., assumes its maximum), and/or for “early” and/or “late”points in time within the T wave, that is, for points in time precedingand/or following the maximum of the T wave and being in the vicinity ofthat maximum (e.g., points falling within a time interval defined by twopoints bracketing the T wave maximum at which the T wave assumes halfits maximum value). In certain embodiments, the early and late times areselected as close as possible to the peak while still beingdistinguishable. A “repolarization peak measure (RPM),” a“repolarization early measure (REM),” and a “repolarization late measure(RLM)” are defined herein as the maximum or minimum signal value of thetime-frequency map at the time where the T wave peaks, the early time,and the late time, respectively.

From one or more repolarization measures (e.g., corresponding to extremaacross frequency at various points in time associated with the T wave)determined for a patient, one or more repolarization indices may becomputed. For example, repolarization measures (such as, e.g., REMs,RLMs, and/or RPMs) may be determined from time-frequency maps computedfrom the ECGs of different leads (signals acquired by differentelectrodes or combinations thereof), and may be averaged across multipleleads, multiple cardiac cycles within each time-frequency map, or both.Left and right ventricular repolarization indices, indicative of thecondition of the left or right ventricles of the heart, may be derivedfrom one or more repolarization measures associated with leadsassociated with the left and right ventricle, respectively, optionallyin conjunction with age- and/or gender-dependent adjustment factorsand/or a measured heart rate. The repolarization indices may bedisplayed or otherwise communicated to a physician (or other clinicallytrained person) to facilitate an assessment of the ventricles'condition, or may be output to an automatic diagnosis algorithm. In someembodiments, repolarization measures or repolarization indices arecompared against each other, or against a threshold, to assess whether,and/or to which degree, heart function is impaired. For example, an RLMexceeding an REM, a right ventricular repolarization index exceeding aleft ventricular repolarization index, or an RLM or REM falling below aspecified threshold may all indicate an abnormality in heart function.

The overall signal level in ECGs, and consequently also thetime-frequency maps derived therefrom, can show significant variationsbetween measurements (e.g., taken at different times) and between leadswithin a measurement that are unrelated to the heart's condition andfunction and, thus, do usually not possess clinical significance.Therefore, to render the data (including ECGs, time-frequency maps,repolarization measures, and repolarization indices) comparable acrossmeasurements, leads, or even patients, the time-frequency map isnormalized, in various embodiments, prior to display and/or to thedetermination of the repolarization measures. Normalization may beapplied to the signed time-frequency map as it results directly fromtime-frequency transform, that is, a time-frequency map generally havingboth positive and negative signal values, or to the unsignedtime-frequency map as it results by taking the absolute value of thetime-frequency transform. Further, the normalization may be uniformlyapplied to the entire time-frequency map, or separately to differentportions thereof (e.g., portions corresponding to individualheartbeats.) The normalization may be based on the difference betweenthe maximum and the minimum of the time-frequency map (in its entirety)or a portion thereof (e.g., a portion limited, in the time dimension, toa time interval corresponding to an integer number of heartbeats, asingle heartbeat, or even only a segment of the ECG signal within aheartbeat). For example, the time-frequency map may be shifted up insignal value by the negative of its minimum value (such that the minimumof the shifted map equals zero), and thereafter scaled based on the(new) maximum value. Typically, the maximum of the time-frequencytransform corresponds to the R peak or the S peak within the QRS complex(which are not always clearly identifiable in each lead), but maximafalling outside the time interval corresponding to the QRS complex arealso possible. In various embodiments, the portion of the time-frequencymap across which a maximum and minimum for normalization are identifiedis chosen to encompass at least the RS segment.

In accordance with various embodiments, the ECGs, time-frequency maps,and/or repolarization indices resulting from heart testing are assembledinto a user interface for display to, e.g., a physician. Thetime-frequency maps may be shown as color maps (which, if based onnormalized signal values, may each span the full color range from red toblue). Since, in general, not all ECGs and associated time-frequencymaps always fit simultaneously within the display of the heart testdevice, the user interface may provide user-input control elements thatallow an operator to select the leads for which ECGs and/ortime-frequency maps are to be displayed, and in which order. The userinterface may further enable the operator to scroll through allavailable leads and, within the ECG and/or time-frequency map for agiven lead, to scroll along the time axis to different portions; in someembodiments, such scrolling can be accomplished via a swiping gesture ona touchscreen display. During scrolling along the time axis, an ECG andits corresponding time-frequency map may be locked so as to both displaythe same limited time range. In some embodiments, the user interfacefurther displays a Glasgow-analysis summary (as known to those ofordinary skill in the art), and/or a graphic icon generated based on thenumerical repolarization indices to provide an intuitive visualindicator of overall heart condition. The icon may, for instance, be orinclude a segmented waveform symbol that signifies, via a number ofgreyed-out segments within an otherwise colored symbol, a degree ofimpairment of heart function (e.g., whether the heart condition isnormal, abnormal, or suspect). The results of ECG testing may bedisplayed within a report screen of a multiple-screen user interfaceconfigured to guide clinical personnel through the electrocardiographyprocess, from patient selection and connection of the patient electrodesthrough the performance of an electrocardiography test to thepresentation of the test results.

The foregoing will be more readily understood from the following moredetailed description, which references the accompanying drawings.

FIG. 1 illustrates, in block-diagram form, various functional componentsof an example system for quantifying and visualization heart conditionin accordance with various embodiments. The system 100 includes one ormore electrodes 102 for acquiring ECG signals (e.g., 10 electrodes for atraditional 12-lead ECG), a processing facility 104 for processing theECG signals, e.g., to obtain time-frequency maps and repolarizationindices, and an electrode interface 106 connecting the electrodes 102 tothe processing facility 104. The electrode interface 106 includescircuitry that outputs electrical signals suitable as input to theprocessing facility 104, e.g., by digitally sampling analog inputsignals. The system 100 further includes a display device 108 foroutputting the ECG test results (including, e.g., the ECGs,time-frequency maps, and/or repolarization indices), and optionallyother input/output devices 109, such as a keyboard and mouse and/or aprinter, for instance. The display device 108 may be a touchscreendoubling as a user-input device. The processing facility 104, electrodeinterface 106, display 108, and input/output devices 109 may beimplemented as a single, stand-alone device implementing allcomputational functionality for ECG signal processing and presentation.Alternatively, they may be provided by the combination of multiplecommunicatively coupled devices. For example, an ECG test device withlimited functionality for recording and/or processing ECG signalsreceived from one or more electrodes 102 via an electrode interface 106of the device may outsource certain computationally intense processingtasks to other computers with which it is communicatively coupled via awired or wireless network. Thus, the functionality of the processingfacility 104 may be distributed between multiple computational devicesthat communicate with each other. Whether provided in a single device ordistributed, the processing facility 104 may be implemented withdedicated, special-purpose circuitry (such as, e.g., a digital signalprocessor (DSP), field-programmable gate array (FPGA), analog circuitry,or other), a suitably programmed general-purpose computer (including atleast one processor and associated memory), or a combination of both.

The processing facility 104 may include various functionally distinctmodules, such as an ECG-signal-processing module 110 that prepares the(e.g., digitally sampled) electrical potentials for display (e.g., byfiltering, smoothing, scaling, etc.) and analysis; a time-frequencytransform module 112 that converts each ECG signal into atwo-dimensional time-frequency map (signed or unsigned) and, optionally,normalizes the time-frequency map; an index-builder module 114 thatanalyzes the ECGs and/or time-frequency maps to determine repolarizationmeasures and/or repolarization indices (which may involve, e.g.,identifying delimiters between successive cardiac cycles, determiningcertain features (such as the QRS complex, T wave, and other segments)within the ECGs, selecting points in time within the T wave, determiningrepolarization measures (such as, e.g., REMs, RLMs, and/or RPMs) fromthe time-frequency maps, reading in any other relevant parameters (suchas gender- or age-based adjustment factors, heart rate, etc.), andcomputing the ventricular indices and/or any functions thereof); ananalysis module 116 that derives further metrics and/or determines heartcondition from the repolarization indices; and a user-interface 118module that generates graphic representations of the data provided bythe other modules and assembles them into a screen for display. TheECG-signal-processing module 110 may be a conventional processing moduleas used in commercially available heart monitors and/or as is capable ofstraightforward implementation by one of ordinary skill in the art. Thetime-frequency transform module 112, index-builder module 114, analysismodule 116, and user-interface module 118 implement algorithms andprovide functionality explained in detail below, and can be readilyimplemented by one of ordinary skill in the art given the benefit of thepresent disclosure.

As will be readily appreciated, the depicted modules reflect merely oneamong several different possibilities for organizing the overallcomputational functionality of the processing facility 104. The modulesmay, of course, be further partitioned, combined, or altered todistribute the functionality differently. The various modules may beimplemented as hardware modules, software modules executed by ageneral-purpose processor, or a combination of both. For example, it isconceivable to implement the time-frequency transform module 112, whichgenerally involves the same operations for each incoming ECG signal,with special-purpose circuitry to optimize performance, whileimplementing the index-builder module 114 and the analysis module 116 insoftware to provide flexibility for adjusting parameters and algorithms,e.g., in response to new medical data.

While the quantification of heart function in accordance herewith is, ingeneral, not limited to any particular number of electrodes, the system100 includes, in various embodiments, ten electrodes 102 to facilitateobtaining a standard twelve-lead ECG, as is routinely used in themedical arts. In accordance with the standard configuration, four of theten electrodes (conventionally labeled LA, RA, LL, RL) are placed on thepatient's left and right arms and legs; two electrodes (labeled V1 andV2) are placed between the fourth and fifth ribs on the left and rightside of the sternum; a further, single electrode (labeled V3) is placedbetween V2 and V4 on the fourth intercostal space; one electrode(labeled V4) is placed between the fifth and sixth ribs at themid-clavicular line (the imaginary reference line that extends down fromthe middle of the clavicle), and, in line therewith, another electrode(labeled V5) is positioned in the anterior axillary line (the imaginaryreference line running southward from the point where the collarbone andarm meet), and the tenth electrode (labeled V6) is placed on the samehorizontal line as these two, but oriented along the mid-axillary line(the imaginary reference point straight down from the patient's armpit).The electric potentials measured by electrodes V1 through V6 correspondto six of the twelve standard leads; the remaining six leads correspondto the following combinations of the signals measured with theindividual electrodes: I=LA−RA; II=LL−RA; III=LL−LA; aVR=RA−½ (LA+LL);aVL=LA−½ (RA+LL); and aVF=LL−½ (RA+LA).

FIG. 2 schematically shows an example ECG 200 for a single cardiaccycle, illustrating the P wave 202, QRS complex 204 (which includes theRS segment 206), and T wave 208. As depicted, the electric potentialusually reaches its maximum 210 at R during the QRS complex 204.However, the polarity of the signal may be inverted (such that the Rpeak has a negative value). Further, in some ECG signals, the S peak hasa greater absolute value than the R peak. In fact, not every ECGunambiguously exhibits the features shown in the (rather typical)example ECG 200. This uncertainty can cause difficulty in attempts tonormalize the signal based on a discrete feature of the ECG such as,e.g., the R peak. To circumvent this difficulty, various embodimentsbase normalization, instead, on a signal maximum and minimum identifiedacross a time range, such as the time interval encompassing at least theRS segment 206 (and thus including both the R and the S peak if theyare, in fact, clearly represented in the signal), irrespective of thefeature to which that maximum or minimum corresponds (if any). FIG. 2also illustrates certain points in time at which data is evaluated inaccordance with various embodiments, such as the time 212 at which the Twave 208 assumes its maximum, and example early and late times 214, 216bracketing the maximum of the T wave. In general, the early and latetimes 214, 216 may be anywhere on the rising edge and falling edge,respectively, of the T wave. In various embodiments, they are selectedwithin ranges between the T wave maximum and points in time precedingand following the T wave maximum, respectively, at which the T waveassumes some specified fraction, e.g., half, of its maximum value.

In accordance herewith, the measured ECGs are transformed intotwo-dimensional time-frequency maps by a suitable mathematicaltransform, such as, for instance, wavelet transform. For a givencontinuous ECG signal x(t), the continuous wavelet transform is givenby:

${{W\left( {a,b} \right)} = {\frac{1}{\sqrt{a}}{\int_{- \infty}^{+ \infty}{\overset{\_}{\psi \left( \frac{t - b}{a} \right)}{x(t)}\ {dt}}}}},$

where ψ is a selected wavelet, b corresponds to a shifted position intime and a to a scaling factor, and W(a, b) is the two-dimensionalfunction of position in time and scale resulting from the transform,also called wavelet coefficients. Similarly, for a discretized ECGsignal x(k) (where k is an integer), the continuous wavelet transform isgiven by:

${{W\left( {a,b} \right)} = {\frac{1}{\sqrt{a}}{\sum\limits_{k}{{x(k)}\left( {{\int_{- \infty}^{{({k + 1})}T}{\overset{\_}{\psi \left( \frac{t - b}{a} \right)}{dt}}} - {\int_{- \infty}^{kT}{\overset{\_}{\psi \left( \frac{t - b}{a} \right)}{dt}}}} \right)}}}},$

where T is the sampling period. The wavelet selected for processing maybe, for example, a Mexican hat wavelet, Morlet wavelet, Meyer wavelet,Shannon wavelet, Spline wavelet, or other wavelet known to those ofordinary skill in the art. Other well-known time-frequency transformsthat may be used alternatively to continuous or discrete wavelettransform include, e.g., the short-term Fourier transform.

The time-frequency maps (such as, e.g., scalograms) generally includeboth positive and negative values. For an intuitive interpretation ofthe signal value of the time-frequency map as a measure of theelectrical energy of the heart, however, the sign is not relevant(since, in a measure of the energy, the electrical potential issquared). Accordingly, in some embodiments, the absolute value of thesignal value (or the square of the signal value) is taken at eachtime-frequency point, resulting in an unsigned time-frequency map. Theunsigned time-frequency map may be advantageous, in particular, fordisplay in a user interface (e.g., to a physician) since it avoidspresenting information that is not of immediate, intuitively discernibleclinical significance and is potentially distracting. On the other hand,since the signed time-frequency map contains generally more informationthan the unsigned time-frequency map, the computation of repolarizationmeasures and indices may (but need not) be based on the signed map.

FIGS. 3A and 3B illustrate an example ECG for a normal heart and anunsigned scalogram resulting from its wavelet transform (followed bytaking the absolute), respectively. In the scalogram, the position bcorresponding to time is along the abscissa and the scale a(corresponding to frequency) along the ordinate, and the signal value Wis encoded by color or intensity (e.g., gray-scale value). As can beseen, the various peaks of the normal ECG are reflected in relativelyhigh intensity in the scalogram, allowing identification of thedifferent ECG segments. For comparison, FIGS. 3C and 3D show an exampleECG and associated scalogram, respectively, for an abnormal heart. Here,features that are prominent in the normal scalogram (e.g., the T wave)have rather low intensity. While this lower intensity generally tracksthe lower values of the T wave in the ECG, it will be appreciated thatthe scalogram may provide better visual clues. Accordingly, thescalogram can aid a physician or other skilled clinician to assess heartfunctioning.

To facilitate meaningful comparisons between time-frequency maps derivedfrom ECGs obtained simultaneously for different leads, thetime-frequency maps may be normalized. Normalization may involve scalingand/or shifting signal values in the time-frequency map to map the rangeof signal values in the map (or at least a portion of the map, asexplained below) to a specified numerical range (hereinafter “targetrange”), e.g., 0 to 255 or −128 to +127 (as are convenient ranges forbinary representations, and can, in turn, be straightforwardly mappedonto color or gray-scale values for display). Using a particularnormalization and the associated target range consistently not onlyacross leads, but also across measurements taken at different timesand/or even for different patients may also serve to improvecomparability of data over time and across the patient population, as iteliminates or at least reduces overall signal-level variations, whichare often not attributable to different heart conditions, allowingphysicians to focus on the clinically relevant relative signal levelswithin a time-frequency map.

The normalization may be based on a regional maximum and minimum definedas the maximum and minimum of the time-frequency map across frequencyand across time within a selected interval, and may then be applied to asecond selected interval that may or may not be the same as the firstselected interval. The maximum and minimum of the time-frequency mapacross frequency and across time within that second selected intervalare hereinafter called the absolute maximum and minimum, and they may,but need not, coincide with the regional maximum and minimum. The firstselected interval is typically, but not required to be, shorter than thesecond selected interval. In some embodiments, the regional maximum andminimum are determined across the entire time-frequency map,corresponding to the entire measurement time of the ECG from which it isderived, and the normalization is applied over that same range (suchthat the first and second selected intervals are equal). In otherembodiments, the regional maximum and minimum are identified within aportion of the time-frequency map that is limited in its time dimension,e.g., to an integer number of heartbeats (e.g., disregarding partialheartbeats) or only a single heartbeat. A time-frequency mapencompassing multiple heartbeats may, for instance, be broken up intoportions corresponding to individual heartbeats, and each portion may benormalized separately (potentially resulting in some discontinuity ofthe signal values in the normalized time-frequency map); in this case,first and second selected intervals are likewise equal to each other.Normalization may even be based on a time interval encompassing onlypart of a heartbeat, selected to likely (but not certainly) include theabsolute maximum and minimum. For instance, in some embodiments,regional maximum and minimum are determined within a portion of atime-frequency map that encompasses at least the RS segment. Note,however, that it is possible for, e.g., the T wave maximum to exceed themaximum in the QRS complex. In cases where the absolute maximum andminimum of the time-frequency map lie outside the portion of the mapacross which the regional maximum and minimum are determined, thenormalization will result in signal values exceeding the target range.(Normalization may also be applied in the time domain. In this case, theregional minimum and maximum are across time over the selected timeinterval.)

Normalization may be applied according to the following equation:

${n = {{\left( {d - d_{\min}} \right)*\frac{\left( {n_{\max} - n_{\min}} \right)}{\left( {d_{\max} - d_{\min}} \right)}} + n_{\min}}},$

where

n is the normalized data point;

n_(min) is the normalized target-range minimum;

n_(max) is the normalized target-range maximum;

d is the data point to be normalized;

d_(min) is the regional minimum; and

d_(max) is the regional maximum.

For example, to map onto the target range from 0 to 255, n_(min) is 0and n_(max) is 255; in effect, this normalization shifts thetime-frequency map to a minimum equal to zero and thereafter scales theshifted map based on its shifted regional maximum. More generally, thenormalization shifts the time-frequency map to a minimum equal ton_(min) and then scales the values of the shifted time-frequency map(taken relative to the minimum value) by the ratio of the differencebetween maximum and minimum of the target range to the differencebetween the regional maximum and minimum.

Normalization can be applied to signed as well as unsignedtime-frequency maps. As will be appreciated, the result of thenormalization will vary depending on whether the underlyingtime-frequency map is signed or unsigned. For example, when mapping asigned time-frequency map with a positive R peak and a negative S peakonto the target range from 0 to 255, several of the frequencies at thepoint in time corresponding to the S peak will map to or near zero.However, when the normalization is applied to the absolute value of theotherwise same time-frequency map, some frequencies at points in timebetween R and S will now map to or near zero whereas several of thefrequencies at the point in time corresponding to the S peak will maponto a relatively larger positive number within the target range.

The time-frequency maps (optionally following normalization) may bedisplayed to a physician for evaluation. Alternatively or additionally,they may be further analyzed, in accordance with various embodiments, todetermine various quantitative indicators of heart condition andfunction. To that end, various measures of the electric activity of theheart can be obtained, e.g., by determining extrema (i.e., maximumand/or minimum values) across frequency of the (normalized)time-frequency map (W or |W|) at certain points (or ranges) in timecorresponding to distinctive features of the underlying ECGs, inparticular, certain points (or ranges) in time associated with the Twave. Measures associated with the T wave are herein referred to as“repolarization measures” and include, for example, the maximum value atan early time within the T wave (REM), the maximum value at a late timewithin the T wave (RLM), or the maximum value at the peak of the T wave(RPM). Additional repolarization measures, e.g., including an integralover a time interval within the T wave, may also be defined and used toquantify heart condition.

From the repolarization measures determined in the time-frequency map,one or more repolarization indices may be derived, e.g., by averaging orbased on information external to the ECG or time-frequency map. Forexample, if the repolarization measures are obtained based on ECGscovering multiple cardiac cycles, the individually determined maxima maybe averaged over these cycles. Further, the various repolarizationmeasures can generally be derived separately from differenttime-frequency maps obtained by transform of ECGs measured for differentrespective leads, and repolarization measures of the same type (e.g.,the REMs) may be averaged across multiple leads. In particular,ventricular repolarization indices may be derived by averaging onlyacross leads associated with the same (i.e., left or right) ventricle.For example, a ventricular index early measure for the right ventricle(VIEM_RV) may be calculated by (e.g., arithmetically) averaging over theREMs of leads V1 and V2, a ventricular index late measure for the rightventricle (VILM_RV) may be calculated by averaging over the RLMs ofleads V1 and V2, and a ventricular index peak measure for the rightventricle (VIPM_RV) may be calculated by averaging over the RPMs ofleads V1 and V2. Similarly, VIEM, VILM, and/or VIPM for the leftventricle (VIEM_LV, VILM_LV, and VIPM_RV) may be calculated by averagingover the REMs, RLMs, and RPMs, respectively, of leads V4, V5, and V6. Incertain embodiments, further indices are derived from the precedingones. For instance, a ventricular index average measure for the rightventricle (VIAM_RV) may be calculated as the sum of VIEM_RV and VILM_RV,divided by the heart rate (measured in beats per minute). Similarly, aventricular index average measure for the left ventricle (VIAM_RV) maybe calculated as the sum of VIEM_LV and VILM_LV, divided by the heartrate. Further, in some embodiments, an index for the heart as a whole iscomputed from respective indices for the left and right ventricles,e.g., by forming the ratio, difference, or some other function of leftand right ventricular indices.

Further, while the repolarization measures are generally indicators ofhow well the heart functions, they can also be affected by age andgender, independently of any abnormal heart condition. To eliminate orat least reduce differences that do not result from heart abnormalities,the repolarization measures may be adjusted, when computingrepolarization indices, with suitable age- and/or gender-dependentfactors. In one embodiment, the adjustment distinguishes merely betweenmale and female patients, using an adjustment factor of 1 for males(i.e., keeping the measures as is) and an adjustment factor smaller thanone (e.g., 1/1.24) for females. In some embodiments, further refinementsare made to distinguish between patients up to forty years old andpatients older than forty years. For example, for females older thanforty years, the adjustment factor may be decreased to 1/1.26. Otherage-based classifications and adjustment factors may be implemented aswell.

FIG. 4 is a flow chart summarizing methods 400 for quantifying andvisualizing heart condition in accordance with various embodiments. Themethod 400 involves measuring one or more ECGs associated with one ormore respective leads (action 402), using one or more electrodes placedon a patient. In some embodiments, ten electrodes are used to obtaintwelve leads. (The phrase “measuring electrocardiograms” is intended toencompass both the acquisition of electrocardiogram signals with theelectrodes, and the digitization and/or initial processing of thesesignals to generate an electrocardiogram for each lead, which mayinclude combining multiple electrocardiogram signals to obtain anelectrocardiogram for a single lead, as described above.) In action 404,the ECG(s) are converted by time-frequency transform (e.g., wavelettransform) into one or more respective two-dimensional time-frequencymaps (e.g., scalograms). The time-frequency map(s) may be used in theoriginal signed form, or converted to unsigned map(s) by taking theabsolute value at each time-frequency point (optional action 406), orboth. Further, the time-frequency map(s) may be normalized (action 408),as described above. In some embodiments, for example, the time-frequencymap is normalized based on the maximum and minimum identified in thetime-frequency map across frequency and across a time intervalencompassing at least the RS segment (and, in some embodiments,encompassing a full cardiac cycle (or heartbeat), multiple (an integernumber of) cardiac cycles, or the entirety of the measurement time).

To visualize the heart condition, a user interface displaying the ECGsand/or corresponding time-frequency maps may be generated (action 410).The signal values in the time-frequency maps may be, e.g., color-codedor represented according to a gray scale. To focus the user's (e.g., aninterpreting physician's) attention on the electrical energy of theheart, it may be beneficial, as indicated above, to present unsigned(i.e., absolute-value) time-frequency maps. Due to spatial constraints,the user interface may, at any given time, display only portions of theECGs and time-frequency maps corresponding to time intervals smallerthan the total measurement time. For example, out of data for atwelve-second interval, the display may be limited to a three-secondsubset. In addition, the number of ECGs and time frequency mapsdisplayed at any given time may be limited, e.g., to three out of twelveECGs and corresponding time-frequency maps. The displayed selection ofECGs and time-frequency map and the displayed time-range may depend on,and be adjusted based on, user input (received at 412). For example, adrop-down menu displayed next to each screen portion allocated to an ECGand time-frequency map may facilitate selection of any of the availableleads. Further, the user may have the ability to scroll through theentire measurement time, e.g., with a conventional scrollbar, or with aswiping gesture performed, with a mouse-controlled cursor or on atouchscreen, in a region displaying an ECG or time-frequency map. Inorder to enable features within an ECG to be properly correlated withfeatures in the corresponding time-frequency map, the displayed portionsare temporally aligned (and, usually, temporally coextensive), and thealignment is retained (or, in other words, “locked in”) as the userscrolls through the ECG or time-frequency map. Further, if ECGs andtime-frequency maps are displayed for multiple leads, they may likewisebe temporally aligned and temporally coextensive, and locked-in in theiralignment as the user scrolls through any one of them.

To quantify heart condition, the time-frequency maps are analyzed inconjunction with the respective ECGs. Specifically, in action 414, oneor more points in time associated with the T wave (e.g., early and latetimes and/or the time where the T wave peaks) are identified within anECG. The corresponding time-frequency map is then analyzed at thesepoints in time to determine, separately at each point in time (or withina small time interval surrounding the respective points in time), amaximum and/or minimum across frequency (action 416). The one or moreextrema across frequency determined in the time-frequency maps at one ormore points in time identified in respective ECGs constituterepolarization measures. Based on these repolarization measures, one ormore repolarization indices can be determined in action 418. Arepolarization index may be based on (and in the simplest case be equalto) a single repolarization measure or combine multiple repolarizationmeasures (e.g., by averaging repolarization measures over leads orcardiac cycles). In addition, the repolarization index may include anadjustment factor that is based on the age or gender of the patient, oron some other characteristic of the patient or circumstance of themeasurement. The computed repolarization indices may be output (inaction 420) in various ways. For example, they may be included in theuser interface (e.g., along with the ECGs and time-frequency maps) fordisplay on-screen or in a printable report, communicated to the user insome other manner, or provided as input to another algorithm.

In some embodiments, the repolarization measures and/or repolarizationindices are automatically analyzed (action 422), based on heuristics orempirical data, to obtain a qualitative assessment of heart condition.For example, based on an expectation that the early repolarizationmeasure is greater than the late repolarization measure, observation ofa late repolarization measure exceeding the early repolarization measure(for the same ECG and time-frequency map) may be taken as a sign ofabnormal or impaired heart function, and communicated as such to theuser. Similarly, since the left ventricular repolarization index shouldbe greater than the right ventricular repolarization index for a healthyheart, the reverse relationship (i.e., a right ventricularrepolarization index greater than the left repolarization index)indicates an abnormality or impairment that may be communicated to theuser. Accordingly, comparisons between repolarization measures andrepolarization indices may be used to assess heart function.Alternatively or additionally, repolarization measures and indices(properly normalized or computed from normalized time-frequency maps)may be compared against empirical thresholds. For example, with anormalization of the time-frequency maps to a range from 0 to 255, anearly or late repolarization measure for the left or right ventriclethat falls below a threshold in the range from 55-75 has been found tocorrelate strongly with some problem in heart function. In someembodiments, one or more repolarization indices are used to determine amyocardial energy category, e.g., distinguishing between high energy(corresponding to no or low functional impairment), moderate energy(corresponding to moderate functional impairment), and low energy(corresponding to high functional impairment). Comparisons ofrepolarization measures and/or repolarization indices against each otheror against specified thresholds in various combinations may also serveto categorize heart function as normal, suspect, or abnormal.

Various modifications of the method 400 may be implemented. For example,as noted above, ventricular indices may be computed based onrepolarization measures determined from values of the time-frequency mapat one or more points in time other than early or late times, and/orover one or more ranges of time. Further, not every action of thedepicted method 400 need be implemented in every embodiment.Accordingly, the depicted method 400 is to be understood as one exampleembodiment only.

FIG. 5 shows an example heart test device 500 in perspective view. Thedepicted device takes the form of a tablet computer 500 including atouchscreen display 502 as well as a control panel 504 with physicalbuttons (e.g., to power the tablet 500 on/off). In some embodiments, asshown, the display 502 presents a multi-tab user interface, explained inmore detail below with respect to FIGS. 6-10. Some of the tabs (shownalong the right edge of the display 502) may be duplicated by thephysical buttons of the control panel 504, allowing an operator tonavigate between different screens and associated device functions indifferent ways. Electrodes for acquiring the ECG signals may be hookedup to the tablet computer 500 via a suitable connector 506 (e.g., a DB15connector). The tablet 500 contains a general-purpose processor andvolatile as well as non-volatile memory storing instructions forimplementing the functional processing modules 110, 112, 114, 116, 118.Of course, in various alternative embodiments, the heart test device maytake different form factors, such as that of a desktop computer, laptopcomputer, or smartphone (to name just a few), each with a suitableelectrode interface, which may include custom circuitry for convertingthe electrode signals into digital signals suitable for furtherprocessing with software. Furthermore, an electrocardiography systemproviding the functionality described herein need not necessarily beimplemented in a single device, but can be provided by multiple devicesused in combination, e.g., a conventional ECG monitor connected to ageneral-purpose computer running software to implement the processingfunctionality described herein.

Turing now to the user interface, FIG. 6 depicts an example home screenof the user interface as it may appear, e.g., when an operator firstturns on the ECG test device 500. The home screen may, for example,provide links to reference materials such as a quick-start guide and amore comprehensive user manual. In accordance with one embodiment, asshown, the user interface includes multiple tabs, corresponding tomultiple respective screens, that are visible in each screen (e.g., onthe right hand side), allowing easy navigation between the screens. Thetabs may be arranged in an order that corresponds to the naturalworkflow through the electrocardiography process, described furtherbelow. For example, in addition to the general tabs for the home screenand a settings screen, the tabs may include, in this order, a patienttab, a test tab, and a report tab.

FIG. 7 illustrates an example report screen in accordance with variousembodiments. As shown, the report screen may be partitioned intomultiple screen portions arranged in an intuitive manner so as to allowthe viewer to quickly locate the desired information. At the top of thescreen, patient information, such as a unique patient identifier and thepatient's name, as well as patient-specific parameters affecting theinterpretation of the ECGs, such as age and gender, may be displayed,along with a record identifier composed of, e.g., a date and time stampfor the test. In a left panel, ECGs and time-frequency maps for one ormore leads may be displayed, e.g., in a vertical arrangement. Thetime-frequency maps can visualize information not discernible from theECGs from which they are derived, e.g., by providing a picture of theelectrical energy of the heart during various stages within the cardiaccycle, and can be useful in detecting conditions such as myocardialischemia, which are traditionally not diagnosed based on ECGs. ECGs areincluded in the display because of their familiarity to physicians andother medical practitioners and for the purpose of identifyingtemporally defined features of the signal, such as the QRS complex and Twave. In accordance with various embodiments, the signal value of thetime-frequency map (e.g., the electrical potential or voltage that isplotted as a function of time and frequency) is encoded in a color scale(or, alternatively, as shown in the black-and-white drawings, in a greyscale). While the signal value itself, as resulting from thetime-frequency (e.g., short-time Fourier or wavelet) transform appliedto the ECG, may be a signed value (generally resulting in both positiveand negative values across the map), the color-coded depicted value maybe unsigned, as obtained from a signed value by computing the absolutevalue. Using unsigned signal values in the color-coded maps serves torepresent the energy level of the time-dependent frequency content,independent of the phase of those frequencies, thus allowing the energyof either positive or negative phase to appear at the same point (alongfrequency) on the time-frequency map.

As described above, the ECGs and time-frequency maps may be analyzed, inaccordance with various embodiments, to provide quantitative indicesindicative of heart health and/or a qualitative assessment orcategorization. The results of the analysis may be presented, as shownin the right panel of FIG. 7, in numerical, textual, and/or graphicform. For example, as shown, the right panel may include an “energyicon” representing the patient's overall heart health, a number ofnumerical indices (e.g., repolarization indices as described above)providing a more detailed picture underneath the icon, and aconventional Glasglow-analysis textual summary underneath the numericalindices. The Glasgow-analysis summary portion may display such metrics,derived from the ECGs, as the patient's heart rate and durations ofcertain ECG features (such as the QRS complex). In addition, it maysummarize the quality and reliability of the test, e.g., based onsignal-to-noise levels of various leads. Glasgow analysis is known tothose of ordinary skill in the art, and will not be further elaboratedupon herein.

FIGS. 8A-8C show the energy icon of FIG. 7 in isolation in threedifferent states, corresponding to high myocardial energy, moderatemyocardial energy, and low myocardial energy, respectively. (These threestates may be interpreted as normal, suspect, and abnormal conditions,respectively.) In the depicted embodiment, the energy icon is asegmented waveform symbol including three segments 800, 802, 804, whichare filled, for a healthy patient (FIG. 8A), with a color gradient(shown, due to the conversion to black-and-white drawings, withvariations in the grayscale value) mirroring the color scale of thetime-frequency maps. For a patient with moderately impaired heartfunction or suspect heart condition (FIG. 7B), the first, left-mostsegment is greyed-out (shown by a uniform grey filling as distinguishedfrom the previous variation). For a patient with strongly impaired orabnormal heart function (FIG. 6C), both the left segment and the middlesegment are greyed out, symbolizing the much lower myocardial energy.The energy icon, thus, provides a clinician with an immediate visualclue as to the patient's heart health. As will be readily appreciated,the energy icon is amenable to finer gradation of the diagnosticassessment if modified to include more than three segments.

For a large number of leads, e.g., for a full twelve-lead ECG, it isgenerally impractical to display all twelve ECGs and associatedtime-frequency maps at once on the display. Accordingly, in variousembodiments, the user is given the ability to scroll vertically throughthe ECG (left) panel to view different ones of the leads. Forillustration, compare FIGS. 7 and 9, for example. While, in FIG. 7, ECGsand time-frequency maps for leads I, II, and III are shown, FIG. 9illustrates the screen in a different scrolling position where, instead,ECGs and time-frequency maps for leads aVL and aVF can be seen.

Alternatively or additionally to being able to scroll through all leads,the user may be given the opportunity to select leads for display foreach of the (sub-)portions of the left panel and thereby specify theorder in which the leads are displayed. In various embodiments, theuser-input controls for lead selection are drop-down menus displayed,initially in their closed state, adjacent the screen portions forrespective ECGs and time-frequency maps. Each drop-down menu lists, onceactivated and opened by the operator, all twelve leads, facilitatinguser selection of any one of the leads for display within the currentscreen portion; FIG. 10 illustrates an opened drop-down menu for thefirst displayed lead. In some embodiments, once a new lead is selected,its position is swapped with the lead that previously occupied therespective screen portion. For example, if lead V1 is changed to lead V5in the drop-down menu, the vertical positions of the respective ECGs andtime-frequency maps will be swapped, and V1 will appear where V5 waspreviously located.

As shown in the report screens depicted in FIGS. 7, 9, and 10, the ECGsmay be displayed with the time axis extending horizontally (as iscustomary). In accordance with various embodiments, the correspondingtime-frequency maps are likewise oriented with their time axes in thehorizontal direction, and are temporally aligned with the ECGs, meaningthat ECG and corresponding time-frequency map both show a given point intime at the same horizontal position. In addition to the temporalalignment within a screen portion showing an ECG and time-frequency mapderived therefrom, the various screen portions displaying different ECGs(and corresponding time-frequency maps) may likewise be temporallyaligned. Further, the left panel (and, indeed, the screen) may not bewide enough to display the ECGs and time-frequency maps in theirentirety, covering the full acquisition period. Instead, the ECGs andtime-frequency maps may be displayed partially, for a limited timerange. The user interface may facilitate, however, a horizontal scrollby the operator through the ECG and/or time-frequency map to affect atemporal shift of the limited time range being displayed. During such ascroll, the ECG and corresponding time-frequency map may be “locked” soas to maintain their temporal alignment. Analogously, the other ECGs andtime-frequency maps within the report screen may be locked to the screenportion being scrolled through, and thus move along with the scrolledthrough ECG/time-frequency map. A scroll can be effected in variousways, such as by a traditional scroll bar. In various embodiments,however, touchscreen capability of the display of the heart monitordevice is exploited to allow scrolling via a swiping gesture performedon-screen in a direction substantially horizontal (and thus parallel tothe time axis of the ECG), within a screen portion displaying the ECGand corresponding time-frequency map. From the swiping gesture, ashifted limited time range may be determined and applied to the shiftingof the displayed ECG/time-frequency map portions. (As will be readilyappreciated by one of ordinary skill in the art, the features oftemporal alignment and temporal locking described above are notcontingent upon the horizontal orientation of the time axis. Rather, itis conceivable that ECGs and/or corresponding time-frequency maps bedisplayed in a horizontal arrangement with their time axes pointingdownward, in which case the temporal alignment would be vertical.)

FIGS. 11A and 11B provide a flowchart illustrating anelectrocardiography workflow 1100 supported by the depicted userinterface, in accordance with various embodiments. The medicalprofessional performing this workflow is, in a typical clinical setting(but not necessarily), a nurse (rather than a physician). Herein, theperson operating the heart monitor device (e.g., to perform the workflowdepicted in FIGS. 11A and 11B, or to subsequently view the results) isgenerically called the “operator.” In FIGS. 11A and 11B, actions of theoperator are shown on the right, and operations performed by the hearttest device are depicted on the left. Referring to FIG. 11A, theoperator, being presented with a multi-tab user interface (action 1102),generally starts by selecting the patient tab (action 1104). On thepatient screen displayed as a result (action 1106), the operator caneither select an existing patient from a list (optionally in conjunctionwith filtering based on operator-supplied search tokens), or create anew patient, e.g., by pressing a “New” button displayed on the screenand entering the relevant patient information (action 1108). Once apatient has been selected, a pop-up message may briefly appear on thepatient screen to confirm the selection (action 1110).

The operator then navigates to the test screen (action 1112). If thepatient has not already been prepped for the test (e.g., electrodes havebeen attached to patient, patient cable has been attached to heartmonitor device and electrodes, etc.), the operator can do so at thisstage (action 1114). Once available, the test screen displays real-timetraces of the ECG signals (action 1116). The operator usually views thereal-time ECG traces to assess whether all the electrodes are connectedand the ECG signals are adequate to proceed with the test. Once theoperator is satisfied with the quality of the real-time traces, he caninitiate a test (action 1118) by pressing, e.g., a “Test” buttonprovided on the test screen. Upon activation, this button may bereplaced by a “Stop/Countdown Timer” button (action 1120) that displaysthe remaining test duration while the test is running, and alsofacilitates operator abortion of the test.

When the ECG test is complete, the user interface automaticallynavigates the operator to the reports screen (action 1122). The reportsscreen may initially (e.g., during the first 15-20 seconds), while theindices and energy icon are being computed, display merely the ECGs andcorresponding time-frequency maps as well as a Glasgow analysis summaryfor viewing by the operator (action 1124). Optionally, a “Calculating .. . ” or similar text message may alert the operator that additionalinformation is forthcoming. An operator may simply wait for thecomputation of the icon and indices to complete. Once the reports screenis updated with the computed indices and icon (action 1126), theoperator may view the results (action 1128). The operator may also begiven the option to print or export the report (e.g., to an external USBdrive) (action 1130). If the operator chooses to print the results (at1128), a print-preview window may allow the operator to navigate thepossibly multiple pages of the report as well as send the report to anetwork or physically attached printer. Printing is useful to allow aphysician (who is not the operator) to view the test results offlinebefore coming back into the exam room to discuss the results with thepatient.

The embodiments describe hereinabove relate to the quantification andvisualization of heart condition based on ECGs in conjunction withtime-frequency maps derived therefrom. Some of the features describedwith reference to time-frequency maps may, however, also apply to, andbe advantageous in the context of, the ECGs themselves. For example, forbetter comparability of the ECGs across leads, measurements, andpatients, the ECGs may be normalized based on the absolute maximum andminimum of the ECG (in its entirety) or a portion thereof. Values of thenormalized ECGs at certain points in time associated with the T wave mayserve as repolarization measures for quantification of heart condition.

Certain embodiments are described herein as including a number of logiccomponents or modules. Modules may constitute either software modules(e.g., code embodied on a non-transitory machine-readable medium or in asignal transmitted over a network) or hardware-implemented modules. Ahardware-implemented module is a tangible unit capable of performingcertain operations and may be configured or arranged in a certainmanner. In example embodiments, one or more computer systems (e.g., astandalone, client or server computer system) or one or more processorsmay be configured by software (e.g., an application or applicationportion) as a hardware-implemented module that operates to performcertain operations as described herein.

In various embodiments, a hardware-implemented module may be implementedmechanically or electronically. For example, a hardware-implementedmodule may comprise dedicated circuitry or logic that is permanentlyconfigured (e.g., as a special-purpose processor, such as a fieldprogrammable gate array (FPGA) or an application-specific integratedcircuit (ASIC)) to perform certain operations. A hardware-implementedmodule may also comprise programmable logic or circuitry (e.g., asencompassed within a general-purpose processor or other programmableprocessor) that is temporarily configured by software to perform certainoperations. It will be appreciated that the decision to implement ahardware-implemented module mechanically, in dedicated and permanentlyconfigured circuitry, or in temporarily configured circuitry (e.g.,configured by software) may be driven by cost and time considerations.

Accordingly, the term “hardware-implemented module” should be understoodto encompass a tangible entity, be that an entity that is physicallyconstructed, permanently configured (e.g., hardwired) or temporarily ortransitorily configured (e.g., programmed) to operate in a certainmanner and/or to perform certain operations described herein.Considering embodiments in which hardware-implemented modules aretemporarily configured (e.g., programmed), each of thehardware-implemented modules need not be configured or instantiated atany one instance in time. For example, where the hardware-implementedmodules comprise a general-purpose processor configured using software,the general-purpose processor may be configured as respective differenthardware-implemented modules at different times. Software mayaccordingly configure a processor, for example, to constitute aparticular hardware-implemented module at one instance of time and toconstitute a different hardware-implemented module at a differentinstance of time.

Hardware-implemented modules can provide information to, and receiveinformation from, other hardware-implemented modules. Accordingly, thedescribed hardware-implemented modules may be regarded as beingcommunicatively coupled. Where multiple of such hardware-implementedmodules exist contemporaneously, communications may be achieved throughsignal transmission (e.g., over appropriate circuits and buses) thatconnect the hardware-implemented modules. In embodiments in whichmultiple hardware-implemented modules are configured or instantiated atdifferent times, communications between such hardware-implementedmodules may be achieved, for example, through the storage and retrievalof information in memory structures to which the multiplehardware-implemented modules have access. For example, onehardware-implemented module may perform an operation, and store theoutput of that operation in a memory device to which it iscommunicatively coupled. A further hardware-implemented module may then,at a later time, access the memory device to retrieve and process thestored output. Hardware-implemented modules may also initiatecommunications with input or output devices, and can operate on aresource (e.g., a collection of information).

The various operations of example methods described herein may beperformed, at least partially, by one or more processors that aretemporarily configured (e.g., by software) or permanently configured toperform the relevant operations. Whether temporarily or permanentlyconfigured, such processors may constitute processor-implemented modulesthat operate to perform one or more operations or functions. The modulesreferred to herein may, in some example embodiments, compriseprocessor-implemented modules.

Similarly, the methods described herein may be at least partiallyprocessor-implemented. For example, at least some of the operations of amethod may be performed by one or processors or processor-implementedmodules. The performance of certain of the operations may be distributedamong the one or more processors, not only residing within a singlemachine, but deployed across a number of machines. In some exampleembodiments, the processor or processors may be located in a singlelocation (e.g., within a home environment, an office environment or as aserver farm), while in other embodiments the processors may bedistributed across a number of locations.

The one or more processors may also operate to support performance ofthe relevant operations in a “cloud computing” environment or as a“software as a service” (SaaS). For example, at least some of theoperations may be performed by a group of computers (as examples ofmachines including processors), these operations being accessible via anetwork (e.g., the Internet) and via one or more appropriate interfaces(e.g., Application Program Interfaces (APIs).)

Example embodiments may be implemented in digital electronic circuitry,or in computer hardware, firmware, software, or in combinations of them.Example embodiments may be implemented using a computer program product,e.g., a computer program tangibly embodied in an information carrier,e.g., in a machine-readable medium for execution by, or to control theoperation of, data processing apparatus, e.g., a programmable processor,a computer, or multiple computers.

A computer program can be written in any form of programming language,including compiled or interpreted languages, and it can be deployed inany form, including as a stand-alone program or as a module, subroutine,or other unit suitable for use in a computing environment. A computerprogram can be deployed to be executed on one computer or on multiplecomputers at one site or distributed across multiple sites andinterconnected by a communication network.

In example embodiments, operations may be performed by one or moreprogrammable processors executing a computer program to performfunctions by operating on input data and generating output. Methodoperations can also be performed by, and apparatus of exampleembodiments may be implemented as, special purpose logic circuitry,e.g., a field programmable gate array (FPGA) or an application-specificintegrated circuit (ASIC).

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other. Inembodiments deploying a programmable computing system, it will beappreciated that that both hardware and software architectures requireconsideration. Specifically, it will be appreciated that the choice ofwhether to implement certain functionality in permanently configuredhardware (e.g., an ASIC), in temporarily configured hardware (e.g., acombination of software and a programmable processor), or a combinationof permanently and temporarily configured hardware may be a designchoice.

FIG. 12 is a block diagram of a machine in the example form of acomputer system 1200 within which instructions for causing the machineto perform any one or more of the methodologies discussed herein may beexecuted. In alternative embodiments, the machine operates as astandalone device or may be connected (e.g., networked) to othermachines. In a networked deployment, the machine may operate in thecapacity of a server or a client machine in server-client networkenvironment, or as a peer machine in a peer-to-peer (or distributed)network environment. While only a single machine is illustrated, theterm “machine” shall also be taken to include any collection of machinesthat individually or jointly execute a set (or multiple sets) ofinstructions to perform any one or more of the methodologies discussedherein. The example computer system 1200 includes one or more processors1202 (e.g., a central processing unit (CPU), a graphics processing unit(GPU) or both), a main memory 1204 and a static memory 1206, whichcommunicate with each other via a bus 1208. The computer system 1200 mayfurther include a video display unit 1210 (e.g., a liquid crystaldisplay (LCD) or a cathode ray tube (CRT)). The computer system 1200also includes an alphanumeric input device 1212 (e.g., a keyboard), auser interface (UI) navigation device 1214 (e.g., a mouse), a disk driveunit 1216, a signal generation device 1218 (e.g., a speaker), a networkinterface device 1220, and a data interface device 1228 (such as, e.g.,an electrode interface 106).

The disk drive unit 1216 includes a machine-readable medium 1222 storingone or more sets of instructions and data structures (e.g., software)1224 embodying or utilized by any one or more of the methodologies orfunctions described herein. The instructions 1224 may also reside,completely or at least partially, within the main memory 1204 and/orwithin the processor 1202 during execution thereof by the computersystem 1200, the main memory 1204 and the processor 1202 alsoconstituting machine-readable media.

While the machine-readable medium 1222 is shown in an example embodimentto be a single medium, the term “machine-readable medium” may include asingle medium or multiple media (e.g., a centralized or distributeddatabase, and/or associated caches and servers) that store the one ormore instructions or data structures. The term “machine-readable medium”shall also be taken to include any tangible medium that is capable ofstoring, encoding, or carrying instructions for execution by the machineand that cause the machine to perform any one or more of themethodologies of the present invention, or that is capable of storing,encoding or carrying data structures utilized by or associated with suchinstructions. The term “machine-readable medium” shall accordingly betaken to include, but not be limited to, solid-state memories, andoptical and magnetic media. Specific examples of machine-readable mediainclude non-volatile memory, including by way of example semiconductormemory devices, e.g., Erasable Programmable Read-Only Memory (EPROM),Electrically Erasable Programmable Read-Only Memory (EEPROM), and flashmemory devices; magnetic disks such as internal hard disks and removabledisks; magneto-optical disks; CD-ROM and DVD-ROM disks, or otherdata-storage devices. Further, the term “machine-readable medium” shallbe taken to include a non-tangible signal or transmission medium,including an electrical signal, a magnetic signal, an electromagneticsignal, an acoustic signal and an optical signal.

The following numbered examples are illustrative embodiments:

1. A method comprising: using one or more electrodes placed on apatient, measuring one or more electrocardiograms associated with one ormore respective leads; converting the one or more electrocardiograms bytime-frequency transform into one or more respective two-dimensionaltime-frequency maps; identifying, within the one or moreelectrocardiograms, one or more points in time associated with a T wave;determining, for at least one of the one or more time-frequency maps,one or more repolarization measures corresponding to extrema acrossfrequency of the respective time-frequency map at the one or more pointsin time associated with the T wave; and outputting at least onerepolarization index based on the one or more repolarization measures.

2. The method of example 1, further comprising normalizing each of theone or more time-frequency maps based at least in part on a differencebetween a maximum and a minimum identified in the respectivetime-frequency map across time in an interval encompassing an RS segmentand across frequency, wherein the one or more repolarization measuresare determined from the normalized time-frequency maps.

3. The method of example 2, wherein normalizing the one or moretime-frequency maps comprises shifting each time-frequency map to aminimum equal to zero and thereafter scaling the respectivetime-frequency map based on the maximum.

4. The method of example 1 or example 2, wherein the time intervalacross which the maximum and minimum are identified in thetime-frequency map encompasses at least one heartbeat.

5. The method of example 1 or example 2, wherein the time intervalacross which the maximum and minimum are identified in thetime-frequency map encompasses a measurement time of the associatedelectrocardiogram in its entirety.

6. The method of example 1 or example 2, wherein the time intervalacross which the maximum and minimum are identified in thetime-frequency map corresponds to an integer number of heartbeats.

7. The method of any one of examples 1-6, wherein the one or more pointsin time associated with the T wave fall within a time interval definedby points preceding and following a maximum of the T wave at which the Twave assumes half of its maximum value.

8. The method of example 7, wherein the one or more points in timeassociated with the T wave comprise a first point in time preceding themaximum of the T wave and a second point in time following the maximumof the T wave.

9. The method of example 8, wherein a first repolarization measurecorresponding to an extremum at the first point in time and a secondrepolarization measure corresponding to an extremum at the second pointin time are determined, the method further comprising comparing thefirst and second repolarization measures.

10. The method of example 9, further comprising determining a heartcondition based on the comparison.

11. The method of example 10, further comprising communicating the heartcondition to a user.

12. The method of example 10 or example 11, wherein an abnormal heartcondition is determined based on the second repolarization measure beinggreater than the first repolarization measure.

13. The method of any one of examples 1-12, wherein electrocardiogramsare measured and respective repolarization measures are determined forat least one lead associated with a left ventricle of the patient'sheart and at least one lead associated with a right ventricle of thepatient's heart, and wherein a left ventricular repolarization indexbased on the at least one repolarization measure determined for the leftventricle is compared with a right ventricular repolarization indexbased on the at least one repolarization measure determined for theright ventricle.

14. The method of example 13, further comprising determining a heartcondition based on the comparison.

15. The method of example 14, further comprising communicating the heartcondition to a user.

16. The method of example 14 or example 15, wherein an abnormal heartcondition is determined based on the right ventricular repolarizationindex being greater than the left ventricular repolarization index.

17. The method of any one of examples 13-16, wherein the leftventricular repolarization index comprises an average over multiplerepolarization measures, corresponding to extrema at a selected one ofthe points in time, determined based on electrocardiograms measured formultiple respective leads associated with the left ventricle, and theright ventricular repolarization index is determined by averaging overmultiple repolarization measures, corresponding to extrema at theselected point in time, determined based on electrocardiograms measuredfor multiple respective leads associated with the right ventricle.

18. The method of any one of examples 1-17, wherein the at least onerepolarization index comprises an average over two or morerepolarization measures.

19. The method of example 18, wherein the average is taken over two ormore heart beats.

20. The method of example 18 or example 19, wherein the average is takenover two or more leads.

21. The method of any one of examples 1-20, wherein the at least onerepolarization index comprises an adjustment factor that is based on atleast one of an age or a gender of the patient.

22. The method of any one of examples 1-21, wherein the at least onerepolarization index is computed from the at least one repolarizationmeasure and a heart rate of the patient.

23. The method of any one of examples 1-22, wherein the time-frequencytransform comprises a wavelet transform and the time-frequency mapcomprises a scalogram.

24. The method of example 23, wherein the time-frequency transformcomprises a continuous wavelet transform.

25. The method of any one of examples 1-24, wherein the time-frequencymaps are absolute-value maps.

26. The method of any one of examples 1-25, further comprisingdetermining a heart condition based on a comparison of the at least onerepolarization index against a threshold.

27. The method of example 26, further comprising communicating the heartcondition to a user.

28. The method of example 26 or example 27, wherein an abnormal heartcondition is determined based on the at least one repolarization indexbeing below the threshold.

29. The method of any one of examples 1-28, wherein the outputtingcomprises displaying the at least one repolarization index in a userinterface.

30. A heart test system comprising: an electrode interface configured toreceive one or more electrocardiogram signals via one or more respectiveelectrodes connectable to the electrode interface; and a processingfacility communicatively coupled to the electrode interface andconfigured to: generate, from the one or more electrocardiogram signals,one or more electrocardiograms for one or more respective leads; convertthe one or more electrocardiograms by time-frequency transform into oneor more respective two-dimensional time-frequency maps; identify, withinthe one or more electrocardiograms, one or more points in timeassociated with a T wave; determine, for at least one of the one or moretime-frequency maps, one or more repolarization measures correspondingto extrema of the respective time-frequency map at the one or morepoints in time associated with the T wave; and output at least onerepolarization index based on the one or more repolarization measures.

31. The system of example 30, wherein the electrode interface and theprocessing facility are integrated into a single heart test device.

32. The system of example 30 or example 31, wherein the processingfacility is configured to implement the method of any one of examples2-29.

33. One or more computer-readable media storing instructions forprocessing one or more electrocardiograms associated with one or morerespective leads, the instructions, when executed by one or morecomputer processors, causing the one or more computer processors to:convert the one or more electrocardiograms by time-frequency transforminto one or more respective two-dimensional time-frequency maps;identify, within the one or more electrocardiograms, one or more pointsin time associated with a T wave; determine, for at least one of the oneor more time-frequency maps, one or more repolarization measurescorresponding to extrema of the respective time-frequency map at the oneor more points in time associated with the T wave; and output at leastone repolarization index based on the one or more repolarizationmeasures.

34. The one or more computer-readable media of example 33, storinginstructions which, when executed by the one or more computerprocessors, cause the one or more computer processors to carry out themethod of any one of examples 2-29.

35. A method comprising: using one or more electrodes placed on apatient, measuring one or more electrocardiograms associated with one ormore respective leads; converting the one or more electrocardiograms bytime-frequency transform into one or more corresponding two-dimensionaltime-frequency maps; and generating a user interface displaying, for atleast one of the one or more electrocardiograms, at least a portion ofthe electrocardiogram and, in temporal alignment therewith, a temporallycoextensive portion of the corresponding time-frequency map.

36. The method of example 35, further comprising: identifying, withinthe one or more electrocardiograms, one or more points in timeassociated with a T wave; determining at least one repolarization indexfrom values of the one or more time-frequency maps at the one or morepoints in time associated with the T wave; and causing the at least onerepolarization index to be displayed in the user interface.

37. The method of example 36, wherein, for multiple leads, multiplerespective electrocardiograms are measured and transformed into multiplecorresponding time-frequency maps, and wherein the generated userinterface displays only a subset comprising fewer than all of themultiple electrocardiograms and corresponding time-frequency maps, theat least one repolarization index being independent from a selection ofelectrocardiograms and time-frequency maps for inclusion in thedisplayed subset.

38. The method of example 36 or 37, wherein generating the userinterface comprises representing unsigned values of the one or moretime-frequency maps based on a color scale, and wherein the at least onerepolarization index is determined from signed values of the one or moretime-frequency maps at the one or more points in time associated withthe T wave.

39. The method of any one of examples 36-38, further comprisingdetermining a heart condition based on the at least one repolarizationindex and generating, for display within the user interface, an iconindicative of the heart condition.

40. The method of example 39, wherein the icon comprises a segmentedwaveform symbol signifying, via a number of greyed-out segments withinthe otherwise colored waveform symbol, a degree of impairment of heartfunction.

41. The method of any one of examples 35-40, wherein the displayedportions of the electrocardiogram and the corresponding time-frequencymap encompass less than an entire measurement time of theelectrocardiogram, the method further comprising temporally shifting,responsive to user input, the displayed portions of theelectrocardiogram and the corresponding time-frequency map.

42. The method of example 41, wherein the displayed portions aretemporally shifted based on user input comprising a scrolling actionassociated with at least one of a screen portion displaying theelectrocardiogram or a screen portion displaying the correspondingtime-frequency map.

43. The method of example 42, wherein the scrolling action comprises aswiping gesture performed within a screen portion displaying theelectrocardiogram or the corresponding time-frequency map and in adirection substantially parallel to a time axis of the electrocardiogramand the corresponding time-frequency map.

44. The method of example 43, wherein the scrolling action is performedon a touchscreen.

45. The method of any one of examples 35-44, wherein the generated userinterface displays at least portions of multiple electrocardiograms andcorresponding time-frequency maps for multiple respective leads, theportions of the electrocardiograms and time-frequency maps for differentones of the leads being temporally coextensive and temporally alignedwith each other.

46. The method of example 45, further comprising temporally shifting,responsive to a scrolling action associated with one of theelectrocardiograms or the corresponding time-frequency map, thedisplayed portions of all of the multiple electrocardiograms andcorresponding time-frequency maps.

47. The method of any one of examples 35-46, wherein, for multipleleads, multiple respective electrocardiograms are measured andtransformed into multiple corresponding time-frequency maps, and whereinthe generated user interface displays only a subset comprising fewerthan all of the multiple electrocardiograms and correspondingtime-frequency maps, the subset being selectable via one or moreuser-input control elements included in the user interface.

48. The method of example 47, wherein the user interface comprisesmultiple screen portions, each facilitating, via an associated one ofthe user-input control elements, user selection of one of the measuredelectrocardiograms and the corresponding time-frequency map for displayin the screen portion.

49. The method of example 48, wherein each of the user-input controlelements comprises a drop-down menu displaying, upon activation,user-selectable symbols for all of the leads.

50. A heart test system comprising: an electrode interface configured toreceive one or more electrocardiogram signals via one or more respectiveelectrodes connectable to the electrode interface; a display device; anda processing facility configured to generate a user interface screenbased at least in part on the received one or more electrocardiogramsignals and to cause display of the user interface screen on the displaydevice, wherein generating and causing display of the user interfacescreen comprises: generating, from the one or more electrocardiogramsignals, one or more electrocardiograms for one or more respectiveleads; converting the one or more electrocardiograms by time-frequencytransform into one or more corresponding two-dimensional time-frequencymaps; generating a user interface displaying, for at least one of theone or more electrocardiograms, at least a portion of theelectrocardiogram and, in temporal alignment therewith, a temporallycoextensive portion of the corresponding time-frequency map.

51. The system of example 50, wherein the electrode interface, thedisplay device, and the processing facility are integrated into a singleheart test device.

52. The system of example 50 or example 51, wherein the display devicecomprises a touchscreen.

53. The system of any one of examples 50-52, wherein the processingfacility is configured to implement the method of any one of examples36-49.

54. One or more computer-readable media storing instructions forprocessing one or more electrocardiograms associated with one or morerespective leads, the instructions, when executed by one or morecomputer processors, causing the one or more processors to: convert theone or more electrocardiograms by time-frequency transform into one ormore corresponding two-dimensional time-frequency maps; and generate auser interface displaying, for at least one of the one or moreelectrocardiograms, at least a portion of the electrocardiogram and, intemporal alignment therewith, a temporally coextensive portion of thecorresponding time-frequency map.

55. The one or more computer-readable media of example 54, storinginstructions which, when executed by the one or more computerprocessors, cause the one or more processors to carry out the method ofany one of examples 35-49.

56. A heart test device comprising: an electrode interface configured toreceive a plurality of electrocardiogram signals via a plurality ofrespective electrodes connectable to the electrode interface; a displaydevice; and a processing facility comprising circuitry configured togenerate a user interface screen based at least in part on the receivedelectrocardiogram signals and to cause display of the user interfacescreen on the display device, wherein generating and causing display ofthe user interface screen comprises: generating for display, based onthe electrocardiogram signals, a plurality of one-dimensionaltime-dependent electrocardiograms for a plurality of respective leads;causing at least partial display of a subset of the electrocardiograms,corresponding to a subset of the leads, in multiple respective screenportions of the user interface screen; causing display, within each ofthe screen portions adjacent the electrocardiogram at least partiallydisplayed therein, of a user-input control element facilitating userselection of any one of the plurality of leads; and in response to userselection of one of the leads via the user-input control elements,causing at least partial display, within the corresponding screenportion, of the electrocardiogram for the selected lead.

57. The device of example 56, wherein the user-input control elementcomprises a drop-down menu displaying, upon activation, user-selectablesymbols for all of the leads.

58. The device of example 56 or example 57, wherein the at leastpartially displayed electrocardiograms are temporally aligned.

59. The device of any of examples 56-58, wherein generating and causingdisplay of the user interface screen further comprises: generating fordisplay, from each of the one-dimensional time-dependentelectrocardiograms for the plurality of leads, a correspondingtwo-dimensional time-frequency map; causing at least partial display ofa subset of the two-dimensional time-frequency maps, corresponding tothe subset of the leads, each time-frequency map of the subset beingdisplayed along with the corresponding electrocardiograms within thecorresponding screen portion; and, in response to user selection of oneof the leads via the user-input control elements, causing at leastpartial display of the time-frequency map for the selected lead in thecorresponding screen portion along with the correspondingelectrocardiogram.

60. A method comprising: measuring a plurality of electrocardiogramsignals using a plurality of respective electrodes placed on a patient;using a processing facility to generate a user interface screen based atleast in part on the received electrocardiogram signals and to causedisplay of the user interface screen on a display device, whereingenerating and causing display of the user interface screen comprises:generating for display, based on the electrocardiogram signals, aplurality of one-dimensional time-dependent electrocardiograms for aplurality of respective leads; causing at least partial display of asubset of the electrocardiograms, corresponding to a subset of theleads, in multiple respective screen portions of the user interfacescreen; causing display, within each of the screen portions adjacent theelectrocardiogram displayed therein, of a user-input control elementfacilitating user selection of any one of the plurality of leads; and inresponse to user selection of one of the leads via the user-inputcontrol elements, causing at least partial display, within thecorresponding screen portion, of the electrocardiogram for the selectedlead.

61. A heart test device comprising: an electrode interface configured toreceive one or more electrocardiogram signals via one or more respectiveelectrodes connectable to the electrode interface; a display device; anda processing facility comprising circuitry configured to generate a userinterface screen based at least in part on the received one or moreelectrocardiogram signals and to cause display of the user interfacescreen on the display device, wherein generating and causing display ofthe user interface screen comprises: generating, from the one or moreelectrocardiogram signals, for each of one or more leads, aone-dimensional time-dependent electrocardiogram; using a time-frequencytransform to compute, from each of the one or more electrocardiograms, acorresponding two-dimensional time-frequency map representing anunsigned signal value as a function of time and frequency; causing, forat least one of the leads, display of temporally aligned portions of theelectrocardiogram and the corresponding time-frequency map, the unsignedsignal value of the time-frequency map being color-coded.

62. A method comprising: presenting, on a display of an electronic heartmonitor device, a multi-tab user interface configured to guide anoperator of the device through a electrocardiography workflow, themulti-tab user interface comprising at least a patient tab, a test tab,and a report tab; in response to operator selection of the patient tab,presenting a patient screen comprising one or more first user-inputcontrol elements facilitating operator selection of a patient among alist of existing patients and one or more second user-input controlelements facilitating operator entry of patient information for a newpatient; in response to operator selection of the test tab and followingconnection of one or more electrodes to the heart monitor device,presenting a test screen comprising one or more real-time traces of oneor more respective electrocardiogram signals measured by the one or moreconnected electrodes and further presenting a third user-input controlelement facilitating operator initiation of an electrocardiogram test;upon operator selection of the third user-input control element, causingacquisition of one or more electrocardiogram signals throughout aspecified test duration and presenting, within the test screen, a fourthuser-input control element displaying a countdown timer based on thespecified test duration and facilitating operator abortion of theelectrocardiogram test; upon completion of the electrocardiogram test,automatically presenting a reports screen associated with the reportstab, the reports comprising report information including at least oneelectrocardiogram computed based on the one or more electrocardiogramsignals and one or more fifth user-input control elements facilitatingoperator initiation of at least one of printing or exporting the reportinformation.

Although the invention has been described with reference to specificexample embodiments, it will be evident that various modifications andchanges may be made to these embodiments without departing from thebroader spirit and scope of the invention. Accordingly, thespecification and drawings are to be regarded in an illustrative ratherthan a restrictive sense.

1. A method comprising: using one or more electrodes placed on apatient, measuring one or more electrocardiograms associated with one ormore respective leads; converting the one or more electrocardiograms bytime-frequency transform into one or more respective two-dimensionaltime-frequency maps; identifying, within the one or moreelectrocardiograms, one or more points in time associated with a T wave;determining, for at least one of the one or more time-frequency maps,one or more repolarization measures corresponding to extrema of therespective time-frequency map at the one or more points in timeassociated with the T wave; and outputting at least one repolarizationindex based on the one or more repolarization measures.
 2. The method ofclaim 1, further comprising normalizing each of the one or moretime-frequency maps based at least in part on a difference between amaximum and a minimum identified in the respective time-frequency mapacross time in an interval encompassing an RS segment and acrossfrequency, wherein the one or more repolarization measures aredetermined from the normalized time-frequency maps.
 3. The method ofclaim 2, wherein normalizing the one or more time-frequency mapscomprises shifting each time-frequency map to a minimum equal to zeroand thereafter scaling the respective time-frequency map based on themaximum.
 4. The method of claim 1, wherein the time interval acrosswhich the maximum and minimum are identified in the time-frequency mapencompasses at least one heartbeat.
 5. The method of claim 1, whereinthe time interval across which the maximum and minimum are identified inthe time-frequency map encompasses a measurement time of the associatedelectrocardiogram in its entirety.
 6. The method of claim 1, wherein thetime interval across which the maximum and minimum are identified in thetime-frequency map corresponds to an integer number of heartbeats. 7.The method of claim 1, wherein the one or more points in time associatedwith the T wave fall within a time interval defined by points precedingand following a maximum of the T wave at which the T wave assumes halfof its maximum value.
 8. The method of claim 7, wherein the one or morepoints in time associated with the T wave comprise a first point in timepreceding the maximum of the T wave and a second point in time followingthe maximum of the T wave.
 9. The method of claim 8, further comprisingcomparing a first repolarization measure corresponding to an extremum atthe first point in time with a second repolarization measurecorresponding to an extremum at the second point in time.
 10. The methodof claim 9, further comprising determining a heart condition based onthe comparison.
 11. The method of claim 10, further comprising causingthe heart condition to be communicated to a user.
 12. The method ofclaim 10, wherein an abnormal heart condition is determined based on thesecond repolarization measure being greater than the firstrepolarization measure.
 13. The method of claim 1, wherein theelectrocardiograms and respective repolarization measures includeelectrocardiograms and repolarization measures for at least one leadassociated with a left ventricle of the patient's heart and at least onelead associated with a right ventricle of the patient's heart, themethod further comprising comparing a left ventricular repolarizationindex determined based on the at least one repolarization measuredetermined for the left ventricle with a right ventricularrepolarization index determined based on the at least one repolarizationmeasure determined for the right ventricle.
 14. The method of claim 13,further comprising determining a heart condition based on thecomparison.
 15. The method of claim 14, further comprising causing theheart condition to be communicated to a user.
 16. The method of claim14, wherein an abnormal heart condition is determined based on the rightventricular repolarization index being greater than the left ventricularrepolarization index.
 17. The method of claim 13, wherein the leftventricular repolarization index comprises an average over multiplerepolarization measures, corresponding to extrema at a selected one ofthe points in time, determined based on electrocardiograms measured formultiple respective leads associated with the left ventricle, and theright ventricular repolarization index is determined by averaging overmultiple repolarization measures, corresponding to extrema at theselected point in time, determined based on electrocardiograms measuredfor multiple respective leads associated with the right ventricle. 18.The method of claim 1, wherein the at least one repolarization indexcomprises an average over two or more repolarization measures.
 19. Themethod of claim 18, wherein the average is taken over two or more heartbeats.
 20. The method of claim 18, wherein the average is taken over twoor more leads.
 21. The method of claim 1, wherein the at least onerepolarization index comprises an adjustment factor that is based on atleast one of an age or a gender of the patient.
 22. The method of claim1, wherein the at least one repolarization index is based on the atleast one repolarization measure and a heart rate of the patient. 23.The method of claim 1, wherein the time-frequency transform comprises acontinuous wavelet transform and the time-frequency map comprises ascalogram.
 24. The method of claim 1, wherein the time-frequency mapsare absolute-value maps.
 25. The method of claim 1, further comprisingdetermining a heart condition based on a comparison of the at least onerepolarization index against a threshold.
 26. The method of claim 25,further comprising causing the heart condition to be communicated to auser.
 27. The method of claim 25, wherein an abnormal heart condition isdetermined based on the at least one repolarization index being belowthe threshold.
 28. The method of claim 1, wherein the outputtingcomprises causing the at least one repolarization index to be displayedin a user interface.
 29. A heart test system comprising: an electrodeinterface configured to receive one or more electrocardiogram signalsvia one or more respective electrodes connectable to the electrodeinterface; and a processing facility communicatively coupled to theelectrode interface and configured to: generate, from the one or moreelectrocardiogram signals, one or more electrocardiograms for one ormore respective leads; convert the one or more electrocardiograms bytime-frequency transform into one or more respective two-dimensionaltime-frequency maps; identify, within the one or moreelectrocardiograms, one or more points in time associated with a T wave;determine, for at least one of the one or more time-frequency maps, oneor more repolarization measures corresponding to extrema of therespective time-frequency map at the one or more points in timeassociated with the T wave; and output at least one repolarization indexbased on the one or more repolarization measures.